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Relationship Between ICU Length of Stay and Long-Term Mortality for Elderly ICU Survivors.

ABSTRACT: To evaluate the association between length of ICU stay and 1-year mortality for elderly patients who survived to hospital discharge in the United States.Retrospective cohort study of a random sample of Medicare beneficiaries who survived to hospital discharge, with 1- and 3-year follow-up, stratified by the number of days of intensive care and with additional stratification based on receipt of mechanical ventilation.None.The cohort included 34,696 Medicare beneficiaries older than 65 years who received intensive care and survived to hospital discharge in 2005.Among 34,696 patients who survived to hospital discharge, the mean ICU length of stay was 3.4 days (± 4.5 d). Patients (88.9%) were in the ICU for 1-6 days, representing 58.6% of ICU bed-days. Patients (1.3%) were in the ICU for 21 or more days, but these patients used 11.6% of bed-days. The percentage of mechanically ventilated patients increased with increasing length of stay (6.3% for 1-6 d in the ICU and 71.3% for ? 21 d). One-year mortality was 26.6%, ranging from 19.4% for patients in the ICU for 1 day, up to 57.8% for patients in the ICU for 21 or more days. For each day beyond 7 days in the ICU, there was an increased odds of death by 1 year of 1.04 (95% CI, 1.03-1.05) irrespective of the need for mechanical ventilation.Increasing ICU length of stay is associated with higher 1-year mortality for both mechanically ventilated and non-mechanically ventilated patients. No specific cutoff was associated with a clear plateau or sharp increase in long-term risk.

SUBMITTER: Moitra VK

PROVIDER: S-EPMC4792682 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Relationship Between ICU Length of Stay and Long-Term Mortality for Elderly ICU Survivors.

Moitra Vivek K VK Guerra Carmen C Linde-Zwirble Walter T WT Wunsch Hannah H

Critical care medicine 20160401 4

<h4>Objectives</h4>To evaluate the association between length of ICU stay and 1-year mortality for elderly patients who survived to hospital discharge in the United States.<h4>Design</h4>Retrospective cohort study of a random sample of Medicare beneficiaries who survived to hospital discharge, with 1- and 3-year follow-up, stratified by the number of days of intensive care and with additional stratification based on receipt of mechanical ventilation.<h4>Interventions</h4>None.<h4>Patients</h4>Th ...[more]

PMID: 26571190

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Project description:Machine learning can predict outcomes and determine variables contributing to precise prediction, and can thus classify patients with different risk factors of outcomes. This study aimed to investigate the predictive accuracy for mortality and length of stay in intensive care unit (ICU) patients using machine learning, and to identify the variables contributing to the precise prediction or classification of patients. Patients (n = 12,747) admitted to the ICU at Chiba University Hospital were randomly assigned to the training and test cohorts. After learning using the variables on admission in the training cohort, the area under the curve (AUC) was analyzed in the test cohort to evaluate the predictive accuracy of the supervised machine learning classifiers, including random forest (RF) for outcomes (primary outcome, mortality; secondary outcome, length of ICU stay). The rank of the variables that contributed to the machine learning prediction was confirmed, and cluster analysis of the patients with risk factors of mortality was performed to identify the important variables associated with patient outcomes. Machine learning using RF revealed a high predictive value for mortality, with an AUC of 0.945 (95% confidence interval [CI] 0.922-0.977). In addition, RF showed high predictive value for short and long ICU stays, with AUCs of 0.881 (95% CI 0.876-0.908) and 0.889 (95% CI 0.849-0.936), respectively. Lactate dehydrogenase (LDH) was identified as a variable contributing to the precise prediction in machine learning for both mortality and length of ICU stay. LDH was also identified as a contributing variable to classify patients into sub-populations based on different risk factors of mortality. The machine learning algorithm could predict mortality and length of stay in ICU patients with high accuracy. LDH was identified as a contributing variable in mortality and length of ICU stay prediction and could be used to classify patients based on mortality risk.

Project description:BACKGROUND:Intensive care unit (ICU) survivors have reduced long-term survival compared to the general population. Identifying parameters at ICU discharge that are associated with poor long-term outcomes may prove useful in targeting an at-risk population. The main objective of the study was to identify clinical and biological determinants of death in the year following ICU discharge. METHODS:FROG-ICU was a prospective, observational, multicenter cohort study of ICU survivors followed 1 year after discharge, including 21 medical, surgical or mixed ICUs in France and Belgium. All consecutive patients admitted to intensive care with a requirement for invasive mechanical ventilation and/or vasoactive drug support for more than 24 h following ICU admission and discharged from ICU were included. The main outcome measure was all-cause mortality at 1 year after ICU discharge. Clinical and biological parameters on ICU discharge were measured, including the circulating cardiovascular biomarkers N-terminal pro-B type natriuretic peptide, high-sensitive troponin I, bioactive-adrenomedullin and soluble-ST2. Socioeconomic status was assessed using a validated deprivation index (FDep). RESULTS:Of 1570 patients discharged alive from the ICU, 333 (21%) died over the following year. Multivariable analysis identified age, comorbidity, red blood cell transfusion, ICU length of stay and abnormalities in common clinical factors at the time of ICU discharge (low systolic blood pressure, temperature, total protein, platelet and white cell count) as independent factors associated with 1-year mortality. Elevated biomarkers of cardiac and vascular failure independently associated with 1-year death when they are added to multivariable model, with an almost 3-fold increase in the risk of death when combined (adjusted odds ratio 2.84 (95% confidence interval 1.73-4.65), p?<?0.001). CONCLUSIONS:The FROG-ICU study identified, at the time of ICU discharge, potentially actionable clinical and biological factors associated with poor long-term outcome after ICU discharge. Those factors may guide discharge planning and directed interventions. TRIAL REGISTRATION:ClinicalTrials.gov NCT01367093 . Registered on 6 June 2011.

Project description:Little is known about the long-term outcomes in elderly survivors of in-hospital cardiac arrest. We determined rates of long-term survival and readmission among survivors of in-hospital cardiac arrest and examined whether these outcomes differed according to demographic characteristics and neurologic status at discharge.We linked data from a national registry of inpatient cardiac arrests with Medicare files and identified 6972 adults, 65 years of age or older, who were discharged from the hospital after surviving an in-hospital cardiac arrest between 2000 and 2008. Predictors of 1-year survival and of readmission to the hospital were examined.One year after hospital discharge, 58.5% of the patients were alive, and 34.4% had not been readmitted to the hospital. The risk-adjusted rate of 1-year survival was lower among older patients than among younger patients (63.7%, 58.6%, and 49.7% among patients 65 to 74, 75 to 84, and ?85 years of age, respectively; P<0.001), among men than among women (58.6% vs. 60.9%, P=0.03), and among black patients than among white patients (52.5% vs. 60.4%, P=0.001). The risk-adjusted rate of 1-year survival was 72.8% among patients with mild or no neurologic disability at discharge, as compared with 61.1% among patients with moderate neurologic disability, 42.2% among those with severe neurologic disability, and 10.2% among those in a coma or vegetative state (P<0.001 for all comparisons). Moreover, 1-year readmission rates were higher among patients who were black, those who were women, and those who had substantial neurologic disability (P<0.05 for all comparisons). These differences in survival and readmission rates persisted at 2 years. At 3 years, the rate of survival among survivors of in-hospital cardiac arrest was similar to that of patients who had been hospitalized with heart failure and were discharged alive (43.5% and 44.9%, respectively; risk ratio, 0.98; 95% confidence interval, 0.95 to 1.02; P=0.35).Among elderly survivors of in-hospital cardiac arrest, nearly 60% were alive at 1 year, and the rate of 3-year survival was similar to that among patients with heart failure. Survival and readmission rates differed according to the demographic characteristics of the patients and neurologic status at discharge. (Funded by the American Heart Association and the National Heart, Lung, and Blood Institute.).

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Dataset Information

Relationship Between ICU Length of Stay and Long-Term Mortality for Elderly ICU Survivors.

Publications

Relationship Between ICU Length of Stay and Long-Term Mortality for Elderly ICU Survivors.

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